Origin provides the following tools to help you summarize your continuous and discrete data.
The Statistics on Columns/Rows operation performs column-wise/row-wise descriptive statistics on selected worksheet data.
Statistics on Columns
Performs column-wise descriptive statistics on grouped or raw data.
Statistics on Rows
Performs row-wise descriptive statistics to generate statistics for rows in worksheet.
Cross tabulation(also known as contingency table) is a table to reveal the frequency distribution of the variables. Analysis based on the table can determine whether there is a significant relationship, obtain the strength and direction of the relationship, and measure and test the agreement of matched-pairs data. It is widely used to analysis categorical data.
Discrete frequency analysis is one common method to analyze discrete variables. It counts the frequency of discrete data, including percentage and cumulative percentage.
The function computes the frequency counts for 1D data and help to produce histogram in desired way.
2D Frequency Count/Binning
A useful tool to compute the frequency counts and plot 2D histogram for 2D/bivariate data.
A normality test is used to determine whether sample data has been drawn from a normally distributed population (within some tolerance).
Six different normality tests are available in Origin:
- D'Agostino's K-Squared
Distribution Fit PRO
Knowing the distribution model of the data helps you to continue with the right analysis. or make estimation of your data. The Distribution Fit tool helps users to examine the distribution of their data, and estimate parameters for the distribution
Correlation Coefficient PRO
The correlation coefficient, also called the cross-correlation coefficient, is a measure of the strength of the relationship between pairs of variables. Origin provides both parametric and non-parametric measures of correlation.
- Pearson's r Correlation
- Spearman's Rank Order Correlation
- Kendall's tau Correlation
Partial Correlation Coefficient PRO
Partial correlation measures the linear relationship between two random variables, after excluding the effects of one or more control variables
An outlier is an observation that is dramatically distant from the rest of the data. Origin provides two tools to help detecting the outliers.
- Grubbs Test
- Dixon's Q-test